Decision support system for equipment selection in construction projects

Efficient and profitable planning for construction projects is highly influenced by the equipment selection for the activities needed in order to accomplish different phases of the projects. This process is particularly more important in heavy construction projects including highways, bridges, tunnels, airports, railroads, dams, river and harbor works, and other major public works where the equipment may be the largest long term capital investment for many companies. This is a very challenging prediction process mainly because of the dynamic nature of the many factors that affect construction projects.; The objective of this research is to develop a tool that will help project administrators select the appropriate equipment and predict the size of fleets for new projects. The most information needed to develop such a system exists in historical data. Regression analysis was employed to extract information and interpret the data into knowledge that can be used to quantify operations for different categories of projects. Then, using descriptive analysis for each type of activity and each given category of the project, the regression results were distributed to the corresponding groups of equipment in order to fulfill the assignment.